The Annals of Statistics

Bayesian Nonparametric Estimation of the Median; Part II: Asymptotic Properties of the Estimates

Hani Doss

Full-text: Open access

Abstract

For data $\theta + \varepsilon_i, i = 1, \ldots, n$ where $\varepsilon_i$ are i.i.d. $\sim F$ with the median of $F$ equal to $0$ but $F$ otherwise unknown, it is desired to estimate $\theta$. In Doss (1985) priors are put on the pair $(F, \theta)$, the marginal posterior distribution of $\theta$ is computed, and the mean of the posterior is taken as the estimate of $\theta$. In the present paper a frequentist point of view is adopted. The consistency properties of the Bayes estimates computed in Doss (1985) are investigated when the prior on $F$ is of the "Dirichlet-type." Any $F$ whose median is 0 is in the support of these priors. It is shown that if the $\varepsilon_i$ are i.i.d. from a discrete distribution, then the Bayes estimates are consistent. However, if the distribution of the $\varepsilon_is$ is continuous, the Bayes estimates can be inconsistent.

Article information

Source
Ann. Statist., Volume 13, Number 4 (1985), 1445-1464.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176349747

Digital Object Identifier
doi:10.1214/aos/1176349747

Mathematical Reviews number (MathSciNet)
MR811502

Zentralblatt MATH identifier
0587.62071

JSTOR
links.jstor.org

Subjects
Primary: 62A15
Secondary: 62G05: Estimation

Keywords
Bayes estimator Dirichlet process prior posterior distribution consistency estimation of the median

Citation

Doss, Hani. Bayesian Nonparametric Estimation of the Median; Part II: Asymptotic Properties of the Estimates. Ann. Statist. 13 (1985), no. 4, 1445--1464. doi:10.1214/aos/1176349747. https://projecteuclid.org/euclid.aos/1176349747


Export citation

See also

  • Part I: Hani Doss. Bayesian Nonparametric Estimation of the Median; Part I: Computation of the Estimates. Ann. Statist., Volume 13, Number 4 (1985), 1432--1444.